C. GABRIEL-ROBEZ

Agriculture Portfolio Manager, Airbus

Everyone knows Airbus, but less about its involvement in the agricultural space – could you elaborate on this?

Airbus is well known for airplanes, but it is also active in the space industry as a satellite manufacturer and as a service provider. We are the oldest commercial satellite imagery provider and serve people who want to get images taken from space over a given area. Historically, most of this activity was driven by defense needs, but we have been active in the agriculture domain almost since the beginning of our journey in the late 1980s. Satellite imagery is very relevant for agriculture, because fields are scattered everywhere on Earth, and satellites can image globally while satellite revisit rates are compliant with crop growth speed.

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Which major challenges in agricultural systems can your offerings (and those of other providers) address?

How widespread is the use of these technologies today and how can they be further scaled up?

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The use of these technologies by agricultural institutions dates back to 1972 with the launch of Landsat 1. Countries like the US and in the EU, as well as Turkey, Mexico and Pakistan etc., have been using imagery from various satellites (SPOT, DMC, Sentinel 2, Landsat…) for decades in order to monitor desertification and food security or follow agricultural policies. Some even installed a Direct Receiving Station (a big space antenna) in order to receive imagery directly or launched their own satellites (India, China, Peru, Thailand…) in order to provide data for their statistics departments.

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Precision agriculture is currently booming. With Sentinel 2 offering free imagery, and increased revisit rates now available on the commercial side, now almost all precision agriculture portal providers are using remote sensing to create variable rate prescription maps and plan field scouting. The scale up here is a matter of revisit rates and image availability. New use cases could also be started with specific spectral bands.

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For insurance and banking, further work is needed in terms of machine learning. Imagery providers also need to unlock access to archive imagery so there is enough data to train the models – and it is not always easy: the oldest datasets were recorded on magnetic tapes!

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How can agricultural value chains and public private partnerships integrate these types of technologies?

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For fertilizer companies, chemical product providers, seeds manufacturers, irrigation asset companies etc, the agricultural value chain is already using satellite imagery today. To further increase the use and the added value, satellite imagery providers need to further streamline access, and offer crop analytics that are accurately describing the crop condition regardless of the satellite used.

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That is what we have been trying to do with our latest product, Verde: simplify the fusion of satellite imagery and agronomy. It provides crop analytics that are easy to ingest in crop models for seamless fusion with other data sources such as soil, moisture and weather information. We know that satellite imagery cannot be the sole information source for agriculture but it is one of the ingredients needed to go beyond observation, establish an agronomic diagnosis, and eventually to release a farming recommendation.